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Understanding the distribution of rock properties in reservoir models is fundamental for planning hydrocarbon exploration and production. The objective of this study is to obtain three-dimensional distribution models of petroelastic facies in a complex carbonate reservoir in the Santos Basin. The Extreme Gradient Boosting (XGBoost) algorithm was applied to classify facies from geophysical well logs and Ocean-bottom nodes (OBN) 3D seismic angle-stack data. Furthermore, additional geological attributes extracted from dataset were used to improve the classification results. The efficiency of XGBoost in the classification of petroelastic facies was verified and the use of these additional attributes is recommended to predict petrophysical or elastic properties in the pre-salt carbonate reservoirs of the Santos Basin.